A genetically modified organism (GMO), such as a genetically-modified plant, is defined at least one transformation event that usually involves the insertion of a heterologous gene construct into the recipient organism. The heterologous gene construct is typically composed of several elements, including at least a gene of interest and regulatory regions for exerting control of gene expression. In addition, the construct may be flanked by DNA sequences from the cloning vector. The majority of genetically-modified plants have been transformed with constructs containing the Cauliflower Mosaic Virus (CaMV) 35S promoter (P-35S) and/or the CaMV 35S terminator (T-35S), or the Agrobacterium tumefaciens nopaline synthase terminator (T-Nos). The most commonly used cloning vectors are derived from pBR322, containing a gene coding for resistance to ampicillin (bla) antibiotics, and vectors containing a gene coding for resistance to neomycin/kanamycin (nptll) antibiotics.
Detection of GMOs may be desired for many reasons. For example, qualitative detection may be used to identify unauthorized GMO material or use of such material. Further, detection may be desired to identify safe or unsafe material, or for the certification of purity of identity-preserved material. Quantitative detection may be used to comply with legal or contractually-agreed thresholds of GMO contamination (e.g., when products of high purity are desired as in the case of organic farming or seed lot certification). Detection may also play a role in safety assessment and risk management by allowing tracing of the GMO material. In many of the foregoing applications, high sensitivity is required for the detection method.
The development of effective analytical methods for transgene detection and identification of GMOs that reduce time and associated costs of analysis has been an extremely active area of research for many years. Morriset et al. (2008) Eur. Food Res. Technol. 227:1287-97. Yet, no adequate strategy has been devised that provides adequate detection capabilities for the many heterologous gene constructs and transformation events currently in use. DNA is the analyte of choice for the routine laboratory detection and quantification of GMOs since it can be effectively detected after extraction from seed, feed or even highly processed food samples.
Preferred current transgene detection methods detect event-specific elements (e.g., transgene sequences) in transgenic plants. Since most of the generic genetic elements integrated in a transgenic event (e.g., promoter, reporter gene, terminator) are frequently used in multiple vectors, tracking specific events by these genetic elements becomes challenging.
Because of the sensitivity desired for detection assays, DNA is typically first amplified by polymerase chain reaction (PCR) from the sample in such an assay. PCR-based GMO detection methods can be Classified according to their level of specificity. Each category corresponds to the identity of the DNA that is amplified in the PCR reaction: (1) screening targets; (2) gene-specific targets; (3) construct-specific targets; and (4) event-specific targets.
The first category of PCR methods (i.e., amplifying screening targets, for example, the P-35S, T-35S, T-Nos, bla, and ornptll genetic elements) have wide applications for detecting transformed material. Matsuoka et al. (2002) J. Agric. Food Chem. 93:35-8. However, these methods cannot be used to identify the GMO, since the presence of the presence of GMO-derived DNA does not necessarily follow from the presence of the screening target. For example, the source of P-35S or T-35S may be naturally-occurring CaMV. Wolf et al. (2000) Eur. Food Res. Technol. 210:367-72.
The second category of PCR methods (i.e., amplifying a gene of interest, for example, the CryIA gene) are more specific than the first category of methods. Vaitilingom et al. (1999) J. Agric. Food Chem. 47:5261-6. There is greater diversity among the genes of interest than among the available (and commonly used) promoters and terminators, and normally a positive signal for the amplification of a specific transgene implies that GM-derived DNA is present in the sample. However, these methods cannot distinguish between different GMOs that may comprise the same gene of interest, such as an herbicide resistance gene. This failing will become more problematic in the future, as common transgenes are stacked together with others in particular combinations that are characteristic of specific GMOs.
The third category of PCR methods targets (i.e., amplifying a junction between adjacent elements of the heterologous gene construct, for example, between the promoter and the gene of interest) provides the only unique signature of a transformation event, within the limitations of present day technology. Zimmerman et al. (1998) Lebensm.-Wiss u Technol. 31: 664-7. Unfortunately, even event-specific methods have their limitations. For example, when two GMOs are crossed (e.g., two different GM maize, such as T25 and Mon810), the resulting hybrid offspring may contain signatures of both events and will therefore be indistinguishable from its two parents in a PCR test. A further onerous limitation of these detection methods is that a specific primer pair is required for each GMO to identify. Moreover, information regarding the construct insertion site is necessary to design primers and conduct the detection assay, which makes detection of uncharacterized GMOs impossible.
New approaches adhere to a general strategy including the selection of an optimal set of different detection methods to search for and identify particular GMOs present in a sample. Querci et al. (2010) Anal. Bioanal. Chem. 396:1991-2002. Recently, a database providing information on optimal detection methods for particular GMOs, and including specific DNA sequences of inserted and flanking elements in many of the GMOs, was provided. Dong et al. (2008) BMC Bioinformatics 9:260. The database is to be updated and increased as new GMOs are introduced and detection methods investigated as a collective task for entities involved in the detection of GMOs. This database is expected to be a useful tool for analytical laboratories performing GMO testing.
In the future, however, GMO detection according to this conventional wisdom will become prohibitively expensive, due to increasing numbers of approved GMO plants, each of which will have its own optimal detection method. Furthermore, it is increasingly common to combine multiple agronomic traits in a single GMO (“gene stacking”). Taverniers et al. (2008) Environ. Biosafety Res. 7:197-218. Gene stacking introduces a difficult challenge to GMO detection. With the exception of testing of single seeds or tissue derived from individual plants, no existing detection method can adequately discriminate between the combined presence of material from two or more single trait GMOs, and single stacked GMOs. Akiyama et al. (2005) J. Agric. Food Chem. 55:5942-7; Holst-Jensen et al. (2006) J. Agric. Food Chem. 54:2799-809; Taverniers et al. (2008), supra.
In recent years, DNA-based detection methods including microarray/chip and multiplex PCRs were explored for the potential for increasing detection assay sensitivity and output, and for identifying stacked GMOs. See, e.g., Tengs et al. (2007) BMC Biotechnol. 7:91. For example, Peano et al. (2005) Anal. Biochem. 346:90-100 and Prins et al. (2008) BMC Genomics 9:584 reported an approach combining a transgene specific ligation reaction, PCR amplification of the ligated oligonucleotide, hybridization, and microarray detection. Multiple oligonucleotide tags immobilized on the microarray surface that targeted the amplified ligation products were used to provide multiplex capabilities in this approach. Such detection methods and multiplexing tools represent the approaches currently used to develop GMO detection methods that address the expectation that sensitive detection will be required in the future from complicated samples containing a diverse plurality of events.